Paper Citation Record · LEDGER

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2501.09384.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.09384 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:10:25.907126Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:45:16.229807Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-16T10:45:16.557653Z

Reference resolution

38 of 38 outbound references displayed

verified exact2
verified fuzzy20
unresolved16
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e443f8d5-7c0e-4ca8-a350-be365b8fd09f · outbound

This paper cites Bridge the Gap between Language models and Tabular Understanding.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Bridge the Gap between Language models and Tabular Understanding

Reference 1

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Observation b5c8466f-9b9c-43d6-a26a-d5fadde0c5da · outbound

This paper cites In: Findings of EACL (2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Findings of EACL (2023)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.270083Z

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Observation 1fe060cf-7f7d-4954-bb74-5e427255589e · outbound

This paper cites an unresolved cited work.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Unresolved cited work

Reference 3

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Observation 92e8349d-de70-46cd-8fab-5839748b1d9c · outbound

This paper cites ACM SIGMOD Record51(1), 33–40 (2022).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval ACM SIGMOD Record51(1), 33–40 (2022)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.253138Z

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Observation d5f04031-1a9c-4f56-a4b6-6fb279d249ff · outbound

This paper cites Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey

Reference 5

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Observation d6631f9a-7ec6-422a-ba17-9efa8af1e00a · outbound

This paper cites In: Scott, D., Bel, N., Zong, C.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Scott, D., Bel, N., Zong, C

Reference 6

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Source-reported events for the cited work

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Observation e34031d4-3b1d-4135-b35d-15b94a848cb1 · outbound

This paper cites In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A

Reference 7

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Observation 5513954e-8ddc-4147-9326-bae2f9ab32e2 · outbound

This paper cites TabLLM: Few-shot Classification of Tabular Data with Large Language Models.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval TabLLM: Few-shot Classification of Tabular Data with Large Language Models

Reference 8

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Observation 0c39190d-1c58-466d-a809-554978b4152d · outbound

This paper cites In: European Conference on Information Retrieval.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: European Conference on Information Retrieval

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.218601Z

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Observation c4c9588a-86dd-45e0-b710-edca7183673c · outbound

This paper cites Sci Data3 (2016).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Sci Data3 (2016)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.198330Z

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Observation 000d899b-104e-4f5a-b8f4-933193e63302 · outbound

This paper cites In: Proceedings of the 44th Annual International ACM SI- GIR Conference on Research and Development in Information Retrieval (SIGIR 2021).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 44th Annual International ACM SI- GIR Conference on Research and Development in Information Retrieval (SIGIR 2021)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.174560Z

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Observation 5be31028-3806-41bc-91dc-10081e38fc5a · outbound

This paper cites In: Findings of the Association for Computational Linguistics: EMNLP 2023.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Findings of the Association for Computational Linguistics: EMNLP 2023

Reference 12

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Observation 68c6b0e6-bdc9-42a4-bbbb-809425eafeb9 · outbound

This paper cites In: The Twelfth International Conference on Learning Representations (2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: The Twelfth International Conference on Learning Representations (2023)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.139015Z

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Observation d4ed650d-24e9-4b0c-9cb0-189c8fb10655 · outbound

This paper cites In: Wang, M., Zitouni, I.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Wang, M., Zitouni, I

Reference 14

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Observation e514c080-456b-414e-8361-135e6e5a3f30 · outbound

This paper cites In: AAAI Conference on Artificial Intelligence (2017), https://api.semanticscholar.org/CorpusID:7672408.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: AAAI Conference on Artificial Intelligence (2017), https://api.semanticscholar.org/CorpusID:7672408

Reference 15

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Observation addbe9bf-0944-429e-80f1-bf4502128ddb · outbound

This paper cites In: Demner-Fushman, D., Ananiadou, S., Thompson, P., Ondov, B.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Demner-Fushman, D., Ananiadou, S., Thompson, P., Ondov, B

Reference 16

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3ea3d85-cbce-4b00-8d98-eea6473db55f · outbound

This paper cites In: Korhonen, A., Traum, D., Màrquez, L.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Korhonen, A., Traum, D., Màrquez, L

Reference 17

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Observation 1b179615-b519-4893-bb66-8261e14b5877 · outbound

This paper cites In: Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020, Pro- ceedings, Part I 42.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020, Pro- ceedings, Part I 42

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.052139Z

Source-reported events for the cited work

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Observation 8d33a63c-bbec-4f51-a46b-858ae6bde619 · outbound

This paper cites In: Carpuat, M., de Marneffe, M.C., Meza Ruiz, I.V.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Carpuat, M., de Marneffe, M.C., Meza Ruiz, I.V

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.034389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 62c19b90-a671-43b9-90bf-a88d1ab08b2b · outbound

This paper cites In: NeurIPS 2023 Second Table Representation Learning Workshop (2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: NeurIPS 2023 Second Table Representation Learning Workshop (2023)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:27.014430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90a84e4e-d470-4c98-b3a9-63ec300aa264 · outbound

This paper cites In: Table Representation Learning Workshop at NeurIPS 2023 (December 2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Table Representation Learning Workshop at NeurIPS 2023 (December 2023)

Reference 21

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Observation 94769df1-cf84-4d19-9485-3b5161d522a1 · outbound

This paper cites TABLET: Learning From Instructions For Tabular Data.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval TABLET: Learning From Instructions For Tabular Data

Reference 22

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Observation b935533c-7438-4ae9-a68c-462873779603 · outbound

This paper cites Journal of Biomedical Informatics113, 103637 (2021).https: //doi.org/https://doi.org/10.1016/j.jbi.2020.103637.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Journal of Biomedical Informatics113, 103637 (2021).https: //doi.org/https://doi.org/10.1016/j.jbi.2020.103637

Reference 23

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Observation 0a0174a3-50c5-494a-b08a-72dcfdd68fb3 · outbound

This paper cites In: Proceedings of the 17th ACM International Conference on Web Search and Data Mining.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 17th ACM International Conference on Web Search and Data Mining

Reference 24

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Observation f6b1e677-8a67-4406-bc39-fb4b44ba1703 · outbound

This paper cites In: Findings of the Association for Computational Lin- guistics: EMNLP 2024 (2024) 16 Author.

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:26.977808Z

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Observation 084ae179-a49e-4cb2-aa4a-51cdcb31fd2c · outbound

This paper cites In: Proceedings of the ACM Web Con- ference 2022.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the ACM Web Con- ference 2022

Reference 26

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Observation e8f583e9-ea52-486e-832e-acd0d7c59c34 · outbound

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Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of The Web Conference 2020

Reference 27

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Observation 65d1c231-083f-4663-9d54-cbacb33de751 · outbound

This paper cites In: Rogers, A., Boyd-Graber, J., Okazaki, N.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Rogers, A., Boyd-Graber, J., Okazaki, N

Reference 28

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Observation 9836fa50-936e-4832-b3f5-c79960780b43 · outbound

This paper cites In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Reference 29

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Observation 2a7bf578-8c32-4d07-922e-c030bded9265 · outbound

This paper cites Emergent Abilities of Large Language Models.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Emergent Abilities of Large Language Models

Reference 30

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Observation 73f370b5-24e7-40e0-8689-41bd9a275d90 · outbound

This paper cites In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Reference 31

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Observation f2c7d008-e423-4f4a-a6fb-0ab91bdf6417 · outbound

This paper cites In: Proceedings of the 46th International ACM SIGIR Con- ference on Research and Development in Information Retrieval.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 46th International ACM SIGIR Con- ference on Research and Development in Information Retrieval

Reference 32

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Observation a645f48e-ab1f-4a38-8ab1-19c08be5d790 · outbound

This paper cites In: The Eleventh International Conference on Learning Representations (2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: The Eleventh International Conference on Learning Representations (2023)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:26.941075Z

Source-reported events for the cited work

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Observation d05345f8-cf70-490f-a33d-5b2d9531e228 · outbound

This paper cites In: Goldberg, Y., Kozareva, Z., Zhang, Y.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Goldberg, Y., Kozareva, Z., Zhang, Y

Reference 34

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Observation a65d5099-2bde-40ad-a239-ca9d97b057d7 · outbound

This paper cites In: Conference on Empirical Methods in Natural Language Processing (2023).

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Conference on Empirical Methods in Natural Language Processing (2023)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:26.923310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11abda4c-09f7-4bdd-8bdb-36e227e13cab · outbound

This paper cites In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:10:26.904820Z

Source-reported events for the cited work

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Observation ce9de480-954c-455c-99d9-55424bcadbdc · outbound

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Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval Unresolved cited work

Reference 630

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Source-reported events for the cited work

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Observation 3687a4f1-2671-4b5a-be61-f877559e4933 · outbound

This paper cites https://doi.org/10.18653/v1/2022.naacl-main.191.

Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval https://doi.org/10.18653/v1/2022.naacl-main.191

Reference 2671

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Pith citing papers

Observation eff9a186-2367-4c01-bb2c-384d76bf579e · inbound

PatientDx: Merging Large Language Models for Protecting Data-Privacy in Healthcare cites this paper.

PatientDx: Merging Large Language Models for Protecting Data-Privacy in Healthcare Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval

Reference 27

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Source-reported events for the cited work

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